1. Field of the Invention
The following description relates to an item recommendation method and apparatus, and more particularly, to an item recommendation method and apparatus to recommend an item that may be preferred by a user based on items rated based on preferences by the user.
2. Description of the Related Art
An item recommendation system may provide functions of selecting at least one item from a plurality of items based on a preference of a user and of recommending the selected item to the user. To select an item that may be preferred by the user, the item recommendation system may collect information about a grade, a purchase, a click or a bookmark associated with an item, and may predict the preference of the user based on the collected information. Also, the item recommendation system may recommend an item to the user in a descending order of preferences for items predicted based on the collected information.
The item recommendation system may need to more carefully and accurately select an item and need to recommend the selected item to the user. In other words, because the user is not able to verify all available items due to constraints of time and money, the user may receive a recommendation for an item from the item recommendation system. Accordingly, the item recommendation system may need to recommend a more accurate item to satisfy the above requirements of the user.
An conventional item recommendation system may recommend an item to a user based on users' preferences inferred from their rated items. Since most users have rated only a few items, the conventional item recommendation system suffers from low accuracy. The users' unrated items can provide more information about users' preferences, but the conventional recommendation system overlooks them. Specifically, some of unrated items are not evaluated (given ratings) by a user because the user is not interested in them.
Accordingly, there is a desire for a method of more accurately predicting a preference of a user and recommending an item to the user based on the predicted preference in an item recommendation system.